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Introduction Bayesian Inference Methods by Heard Nick (30 results)
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An Introduction to Bayesian Inference, Methods and Computation
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An Introduction to Bayesian Inference, Methods and Computation
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An Introduction to Bayesian Inference, Methods and Computation
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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An Introduction to Bayesian Inference, Methods and Computation
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Introduction to Bayesian Inference, Methods and Computation
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Add to basketPaperback. Condition: Brand New. 181 pages. 9.25x6.10x0.71 inches. In Stock.
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Introduction to Bayesian Inference, Methods and Computation
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer International Publishing, Springer Nature Switzerland, 2022
ISBN 10: 3030828107 ISBN 13: 9783030828103
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.
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Taschenbuch. Condition: Neu. An Introduction to Bayesian Inference, Methods and Computation | Nick Heard | Taschenbuch | xii | Englisch | 2022 | Springer | EAN 9783030828103 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Add to basketHardcover. Condition: Brand New. 169 pages. 9.75x6.50x0.50 inches. In Stock.
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer International Publishing, Springer Nature Switzerland, 2021
ISBN 10: 3030828077 ISBN 13: 9783030828073
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.
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Condition: new. Questo è un articolo print on demand.
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Condition: new. Questo è un articolo print on demand.
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer International Publishing, Springer Nature Switzerland Okt 2022, 2022
ISBN 10: 3030828107 ISBN 13: 9783030828103
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches. 184 pp. Englisch.
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030828107 ISBN 13: 9783030828103
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synony.
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer International Publishing, Springer International Publishing Okt 2021, 2021
ISBN 10: 3030828077 ISBN 13: 9783030828073
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches. 184 pp. Englisch.
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer, Palgrave Macmillan Okt 2022, 2022
ISBN 10: 3030828107 ISBN 13: 9783030828103
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 184 pp. Englisch.
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2021
ISBN 10: 3030828077 ISBN 13: 9783030828073
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes.
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Condition: New. PRINT ON DEMAND.
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An Introduction to Bayesian Inference, Methods and Computation
Language: English
Published by Springer, Palgrave Macmillan Okt 2021, 2021
ISBN 10: 3030828077 ISBN 13: 9783030828073
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 184 pp. Englisch.
